Approximation Models on Economic Production Quantity with Learning Effect

碩士 === 國立屏東科技大學 === 工業管理系所 === 97 === There was learning effect in the past relevant production references.Part of the processing separate accumulation productive time or cost, usually were calculated conveniently, however, it was approximated by the continuous integral in the real value as well, fo...

Full description

Bibliographic Details
Main Authors: Luo,Wu-Chen, 駱武謙
Other Authors: Wu,Ji-Cheng
Format: Others
Language:zh-TW
Online Access:http://ndltd.ncl.edu.tw/handle/08268826365293015825
Description
Summary:碩士 === 國立屏東科技大學 === 工業管理系所 === 97 === There was learning effect in the past relevant production references.Part of the processing separate accumulation productive time or cost, usually were calculated conveniently, however, it was approximated by the continuous integral in the real value as well, for example: Accumulation of productive time Log-Linear Model The researchers took notices of that the above approximate error. They proposed that other integral approach models, and attempted to control between the real value error, but they also brought the question as following, they inferred the EPQ model with the economic production quantity, the mathematical computation will become complex, the value solved difficulties and relatively increases. In the light of the decision-maker, the final goal they cared about were the EPQ pattern decision variables and economic production batch, production cycle and unit total cost; So far, not any of the researchers has carried on systematization's appraisal in view of the different comparatively Therefore, the present paper in view of this integral approaches the model to these decision-making variable influences and research gaps, the discussion Log-Linear learning curves, the analysis compare of integral approach model of several kinds of accumulation productive time, is related to the decision variable of the EPQ pattern with the impact, which takes references of the production decision-making.